Exact prediction and consumption of residential electricity power cost hours, daily, weekly, monthly using ant, ML and DL techniques /
Title
Exact prediction and consumption of residential electricity power cost hours, daily, weekly, monthly using ant, ML and DL techniques /
Subject
Communication
Description
Patent Number: 202241055650, Applicant: Dr. S Perumal.
This research describes an unique method for predicting energy consumption based on deep neural networks that can accurately estimate the hourly energy consumption profile of a residential building one day in advance, taking occupancy into account. Providers of energy and utilities can determine the most efficient generation schedule if they have an accurate evaluation of the quantity of energy utilised by houses. A comprehensive review of a number of criteria was undertaken in order to initiate an investigation into the various energy estimation techniques that employ machine learning.
This research describes an unique method for predicting energy consumption based on deep neural networks that can accurately estimate the hourly energy consumption profile of a residential building one day in advance, taking occupancy into account. Providers of energy and utilities can determine the most efficient generation schedule if they have an accurate evaluation of the quantity of energy utilised by houses. A comprehensive review of a number of criteria was undertaken in order to initiate an investigation into the various energy estimation techniques that employ machine learning.
Creator
Das, Tapas.
Publisher
Intellectual Property India
Date
2022
Language
English
Type
Patent
Collection
Citation
Das, Tapas., “Exact prediction and consumption of residential electricity power cost hours, daily, weekly, monthly using ant, ML and DL techniques /,” CHRIST (Deemed To Be University) Institutional Repository, accessed September 20, 2024, https://archives.christuniversity.in/items/show/2789.